Blog.

Provocative title, I know... but I have learned so much about the misuse of this forecast error measure this past year and I would like to share with you what I've learned and what you can use instead of MAPE. The Problem Most companies rely on forecast accuracy metrics such as MAPE (Mean Absolute Percentage Error) and RMSE (Root Mean Squared Error) to evaluate how well their demand forecasts perform. These measures are intuitive and easy to communicate, but they become misle

Can social media predict product demand?   Many supply chain professionals still rely on traditional forecasting methods, but what if social media could give us real-time demand signals before sales even happen? In my recent research, we found that analyzing social media sentiment and engagement can improve demand forecasting accuracy by 42%, especially for new products with no historical data. Let’s break it down. The Challenge: Forecasting New Product Demand is Unpredictabl

The Psychology of Algorithm Aversion and How AI Can Enhance Judgmental Decision-Making Artificial intelligence (AI) is transforming business decision-making, offering unprecedented speed and accuracy in areas like forecasting, risk assessment, and operational planning. Yet, when faced with a choice between an AI-generated prediction and human judgment, many decision-makers still favor human expertise, even when the AI is demonstrably more accurate. This paradox raises an impo